icon-agents

🥈Silver

Icon Agents provides a collection of 64 AI agents across 8 domains, enabling developers to access expert-level programming wisdom. It integrates with Claude Code, allowing for intelligent multi-domain analysis and direct LLM expert selection. Ideal for streamlining development workflows and enhancing productivity.

1630Updated Today

Intermediate30min to implementautomation

Saves ~15 min per use

Quick InstallView Source

git clone https://github.com/Commands-com/icon-agents.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/Commands-com/icon-agents

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I need to use an Icon Agent to [SPECIFIC TASK]. Which agent would be best suited for this task? Provide a step-by-step guide on how to use this agent effectively. Also, suggest any additional agents that might complement this task.

Example Output

Based on your request to optimize a Python script for handling large datasets, the best Icon Agent for this task would be the 'Python Optimization Agent'. Here's a step-by-step guide on how to use this agent effectively:

1. **Initial Setup**: Start by providing the agent with the current version of your Python script. Make sure to include any specific libraries or dependencies you're using.
2. **Task Definition**: Clearly define the optimization goals. For example, you might want to reduce memory usage, improve processing speed, or both.
3. **Agent Interaction**: The agent will analyze your script and suggest optimizations. It might recommend using more efficient data structures, implementing parallel processing, or leveraging specific libraries for large dataset handling.
4. **Implementation**: Apply the suggested changes to your script. The agent can provide code snippets and explanations for each optimization.
5. **Testing and Iteration**: Test the optimized script and provide feedback to the agent. The agent can further refine its suggestions based on your test results.

Additional agents that might complement this task include the 'Data Analysis Agent' for evaluating the performance impact of the optimizations and the 'Code Review Agent' for ensuring the overall quality and maintainability of your script.